Received 17.07.2025
Revised 11.11.2025
Accepted 15.12.2025
Retrieved from Iss. 118, P. 2, 2025
Pages 148 -158
Abstract
Current scientific research demonstrates a tendency to use artificial intelligence for solving tasks in various fields of human activity. For example, tasks are addressed in geodesy for the automation of office processing of spatial data, in geographic information systems for the creation of vector models using machine learning, and in land management for the development of more automated systems of interaction with people. However, certain interdisciplinary tasks, whose solutions require unconventional approaches, must be addressed at a higher level of information generalization. The highest level of generalization is essential for solving problems in legislative bodies, where laws are formulated that apply to all activities within the country. The above considerations lead to the idea of creating a special intelligent system whose knowledge base would include a model of conditionally noospheric intelligence. The term conditionally noospheric intelligence is introduced here because V. I. Vernadsky, in his doctrine of the noosphere, argued that all humanity on planet Earth influences its biosphere and that a collective mind, which he referred to as a «geological force» is necessary for the evolutionary transformation of the biosphere into the noosphere. Unfortunately, the impact of humanity on the Earth’s biosphere is currently insufficiently studied. Nevertheless, the authors of this work attempt to develop an approach that would allow higher-quality interaction among specialists who are geographically distant and lack direct connections. The purpose of this research is to provide a scientific rationale for the formation of the concept of conditionally noospheric intelligence using ontological and geographic information modeling to utilize the qualification potential of academic and teaching staff. Applying certain limitations and assumptions, the study examines the system’s ability to systematically form groups of experts from among the intellectual elite, experts in their respective fields, to solve practical tasks and contemporary problems, with mathematical justification and representing scientific potential through a quantitative model constructed using geographic information technologies. Additionally, in this work, the intellectual elite refers to academic and teaching staff of higher educational institutions who have the appropriate specialization and a high qualification potential in their field of knowledge. Such a model may operate using artificial intelligence and information technologies but is not limited to them. The study employs methods of system and functional analysis, as well as formal representations from set theory and utility theory, with the application of ontological and geographic information modeling. As a result of the research, the term conditionally noospheric intelligence was introduced. For the first time, a conceptual representation of conditionally noospheric intelligence has been formulated. A core of conditionally noospheric intelligence has also been developed in the form of a mathematical model. Examples of potential applications of conditionally noospheric intelligence are presented using geographic information systems and illustrated within the field of geodesy.
Keywords:
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